Enhancing Adaptive Behavioral Interventions with LLM Inference from Participant-Described States

This repository contains the official implementation for LLM4TS and StepCountJITAI+LLM, from the paper: Enhancing Adaptive Behavioral Interventions with LLM Inference from Participant-Described States, Karine Karine and Benjamin M. Marlin, 2025.

This paper was accepted at MLHC 2025.

• arXiv link: https://arxiv.org/abs/2507.03871

• paper link: https://github.com/reml-lab/llm4ts/tree/main/LLM4TS_paper.pdf

• poster link: https://github.com/reml-lab/llm4ts/tree/main/LLM4TS_poster.pdf

Examples

See the examples directory for a list of examples that can be run locally or launched in Google Colab.

For example:

• LLM4TS and StepCountJITAI+LLM QuickStart

Citing this paper

@inproceedings{LLM4TS2025, 
title = {Enhancing Adaptive Behavioral Interventions with LLM Inference from Participant-Described States},
author={Karine Karine and Benjamin M. Marlin},
booktitle = {Machine Learning for Healthcare (MLHC) 2025,
year = {2025},
}